Entanglement reciprocation between qubits and continuous variables

We investigate how entanglement can be transferred between qubits and continuous variable (CV) systems. We find that one ebit borne in maximally entangled qubits can be fully transferred to two CV systems which are initially prepared in pure separable Gaussian field with high excitation. We show that it is possible, though not straightforward, to retrieve the entanglement back to qubits from the entangled CV systems. The possibility of deposition of multiple ebits from qubits to the initially unentangled CV systems is also pointed out.Comment: 4 pages, 3 figures, RevTeX

Universal Quantum Information Compression

Suppose that a quantum source is known to have von Neumann entropy less than or equal to S but is otherwise completely unspecified. We describe a method of universal quantum data compression which will faithfully compress the quantum information of any such source to S qubits per signal (in the limit of large block lengths).Comment: RevTex 4 page

Accumulation of entanglement in a continuous variable memory

We study the accumulation of entanglement in a memory device built out of two continuous variable (CV) systems. We address the case of a qubit mediating an indirect joint interaction between the CV systems. We show that, in striking contrast with respect to registers built out of bidimensional Hilbert spaces, entanglement superior to a single ebit can be efficiently accumulated in the memory, even though no entangled resource is used. We study the protocol in an immediately implementable setup, assessing the effects of the main imperfections.Comment: 4 pages, 3 figures, RevTeX

Strong-driving-assisted multipartite entanglement in cavity QED

We propose a method of generating multipartite entanglement by considering the interaction of a system of N two-level atoms in a cavity of high quality factor with a strong classical driving field. It is shown that, with a judicious choice of the cavity detuning and the applied coherent field detuning, vacuum Rabi coupling produces a large number of important multipartite entangled states. It is even possible to produce entangled states involving different cavity modes. Tuning of parameters also permits us to switch from Jaynes-Cummings to anti-Jaynes-Cummings like interaction.Comment: Last version with minor changes and added references. Accepted for publication in Phys. Rev. Letter

Thermodynamic equilibrium and its stability for Microcanonical systems described by the Sharma-Taneja-Mittal entropy

It is generally assumed that the thermodynamic stability of equilibrium state is reflected by the concavity of entropy. We inquire, in the microcanonical picture, on the validity of this statement for systems described by the bi-parametric entropy $S_{_{\kappa, r}}$ of Sharma-Taneja-Mittal. We analyze the ``composability'' rule for two statistically independent systems, A and B, described by the entropy $S_{_{\kappa, r}}$ with the same set of the deformed parameters. It is shown that, in spite of the concavity of the entropy, the ``composability'' rule modifies the thermodynamic stability conditions of the equilibrium state. Depending on the values assumed by the deformed parameters, when the relation $S_{_{\kappa, r}}({\rm A}\cup{\rm B})> S_{_{\kappa, r}}({\rm A})+S_{_{\kappa, r}}({\rm B})$ holds (super-additive systems), the concavity conditions does imply the thermodynamics stability. Otherwise, when the relation $S_{_{\kappa, r}}({\rm A}\cup{\rm B})<S_{_{\kappa, r}}({\rm A})+S_{_{\kappa, r}}({\rm B})$ holds (sub-additive systems), the concavity conditions does not imply the thermodynamical stability of the equilibrium state.Comment: 13 pages, two columns, 1 figure, RevTex4, version accepted on PR

Using Soil Attributes and GIS for Interpretation of Spatial Variability in Yield

Precision farming application requires better understanding of variability in yield patterns in order to determine the cause-effect relationships. This field study was conducted to investigate the relationship between soil attributes and corn (Zea mays L.)-soybean (Glycine max L.) yield variability using four years (1995-98) yield data from a 22-ha field located in central Iowa. Corn was grown in this field during 1995, 1996, and 1998, and soybean was grown in 1997. Yield data were collected on nine east-west transects, consisting of 25-yield blocks per transect. To compare yield variability among crops and years, yield data were normalized based on N-fertilizer treatments. The soil attributes of bulk density, cone index, organic matter, aggregate uniformity coefficient, and plasticity index were determined from data collected at 42 soil sampling sites in the field. Correlation and stepwise regression analyses over all soil types in the field revealed that Tilth Index, based upon soil attributes, did not show a significant relationship with the yield data for any year and may need modifications. The regression analysis showed a significant relationship of soil attributes to yield data for areas of the field with Harps and Ottosen soils. From a geographic information system (GIS) analysis performed with ARC/INFO, it was concluded that yield may be influenced partly by management practices and partly by topography for Okoboji and Ottosen soils. Map overlay analysis showed that areas of lower yield for corn, at higher elevation, in the vicinity of Ottosen and Okoboji soils were consistent from year to year; whereas, areas of higher yield were variable. From GIS and statistical analyses, it was concluded that interaction of soil type and topography influenced yield variability of this field. These results suggest that map overlay analysis of yield data and soil attributes over longer duration can be a useful approach to delineate subareas within a field for site specific agricultural inputs by defining the appropriate yield classes

An information theoretic approach to statistical dependence: copula information

We discuss the connection between information and copula theories by showing that a copula can be employed to decompose the information content of a multivariate distribution into marginal and dependence components, with the latter quantified by the mutual information. We define the information excess as a measure of deviation from a maximum entropy distribution. The idea of marginal invariant dependence measures is also discussed and used to show that empirical linear correlation underestimates the amplitude of the actual correlation in the case of non-Gaussian marginals. The mutual information is shown to provide an upper bound for the asymptotic empirical log-likelihood of a copula. An analytical expression for the information excess of T-copulas is provided, allowing for simple model identification within this family. We illustrate the framework in a financial data set.Comment: to appear in Europhysics Letter

Variational Principle underlying Scale Invariant Social Systems

MaxEnt's variational principle, in conjunction with Shannon's logarithmic information measure, yields only exponential functional forms in straightforward fashion. In this communication we show how to overcome this limitation via the incorporation, into the variational process, of suitable dynamical information. As a consequence, we are able to formulate a somewhat generalized Shannonian Maximum Entropy approach which provides a unifying "thermodynamic-like" explanation for the scale-invariant phenomena observed in social contexts, as city-population distributions. We confirm the MaxEnt predictions by means of numerical experiments with random walkers, and compare them with some empirical data

Comparing Field Methods that Estimate Mobile–Immobile Model Parameters

Recent studies have used field techniques that estimate soil hydraulic and solute transport parameters. These methods utilize a tension infiltrometer to infiltrate either a single tracer or a series of tracers in order to estimate immobile water content (θim) and mass exchange coefficient (α) of the mobile–immobile solute transport model. The objective of this study was to compare two single tracer methods (basic and variance) with one multiple tracer method for estimating θim and α from data obtained on the same field soil location. Hydraulic conductivity (K(h 0)) was also estimated using these methods. Research was done at five interrow sites in a ridge-tilled corn (Zea mays L.) field, and the soil was mapped as a Nicollet series (fine-loamy, mixed, superactive, mesic, Aquic Hapludoll). The values of θim and α estimated by the multiple tracer method compared well with previously measured values using the same technique on the same field. The θim values for the multiple tracer technique were larger than values derived from the basic single tracer technique. The basic single tracer technique did not take into consideration a mass exchange between θim and the mobile water domain (θm). The α values were less variable for the multiple tracer method than for the single tracer-variance method. Values of immobile water fraction (θim/θ) for the multiple and basic single tracer techniques ranged from 0.30 to 0.52 and from 0.24 to 0.35, respectively. The values of α for the multiple and single tracer-variance techniques ranged from 0.06 to 0.9 d−1 and from 0.03 to 60 d−1, respectively. The volumetric water content (θ) changed considerably over the course of the experiment for the estimation of α using the single tracer-variance method; thus, the assumptions of this technique were compromised. The measured values of K(h 0) at the five sites ranged from 0.47 to 1.66 μm s−1 There was evidence that the basic single tracer method underestimated θim and overestimated θm, because this method considers α = 0 during the tracer application

Spatial Variability Analysis: A First Step in Site-Specific Management

Small-scale spatial variability of selected soil-test parameters in two adjacent central Iowa fields is discussed. We used semivariance analysis to detect the distance to which parameters were correlated and to estimate the strength of each correlation. Distinct differences in spatial dependence patterns were observed for the two farming systems